Building fires can be considered a risk to the health and safety of occupants. Environmental factors in building fires might affect the speed of an evacuation. Therefore, in this study participants (N = 153) were tested in an experimental design for the effects of (1) a fire alarm, (2) darkness and (3) the use of emergency exit signs on building evacuation time. In addition, the effects of age and gender on evacuation time were investigated. The main results indicate that the combination of a fire alarm, darkness and not illuminated emergency exit signs had a significant negative influence on evacuation time, namely an increase in evacuation time of 26.6% respectively 28.1%. Another important finding is that age had a significant negative effect on evacuation time. The increase in evacuation time was at least 30.4% for participants aged 56 years or older compared to participants aged 18–25 years. For gender no significant effect was found. Building and safety managers can use these results by including longer evacuation time considerations – based on darkness and older age – in their evacuation plans. Future research should focus further on investigating the effects of personal and psychological characteristics on evacuation behaviour and evacuation time.

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Sexually transgressive behaviour (STB) causes serious problems for, among others, students of higher education. The persuasive card game TALK THAT TALK was designed to promote ethical bystander behaviour in STB situa-tions and contribute to a social transition to less sexual violence. To this aim, the game facilitates Intergroup Dialogues between female and male players. A con-trolled experiment was conducted to evaluate the game. The outcome variables of the experiment were obtained from the literature: Willingness to Intervene, Awareness of prevalence of STB, and Bystander Responsibility. Quantitative and qualitative analyses, including validated questionnaires and semi-structured in-terviews, were employed to measure the game’s effects. Participants evaluated the quality of the game (session) and game experience positively and reported that meaningful intergroup dialogues about STB situations took place during the game session. As a result, in the experimental group a significant increase of the three outcome variables was observed, whereas in the control group a non-sig-nificant decrease was found. However, due to a selection bias in the recruitment of participants the effects were possibly overestimated. Reversely, a lack of prac-tical skills training in the game may have led to an underestimation of the effects. We concluded that the game TALK THAT TALK may promote ethical bystander behaviour in STB situations by facilitating an intergroup dialogue between fe-male and male participants. Future research should establish if the results can be generalised to a more representative sample of participants and if the game ef-fects may be improved when institutes for higher education include the game in large-scale intervention programmes against sexually transgressive behaviour.@en

Different leader-follower behaviors may be observed in models, such as group gathering, backtracking, and changing between groups. However, a comparison of these behaviors resulting in possible substantially different estimates of optimal evacuation procedures is lacking. Hence, we developed an agent-based model in combination with exploratory modeling to compare backtracking, group gathering, and followers changing leaders and investigate their influence on the evacuation and response time. The simulation results showed that backtracking and changing of groups increased the evacuation time. Whereby group gathering increase the response time. In addition, the combination of behaviors increases the influence on evacuation and response time. Further research needs to test these results with empirical studies and investigate the impact of other leader-follower behavior. The found insights may be utilized in evacuation research for modeling this behavior and they provide a valuable basis for designing policies in buildings with a high distribution of leader-follower groups.@en

“How does culture, in combination with cues, settings and affiliation, influence response-phase behaviour and time and total evacuation time?”. A questionnaire and an agent-based model for a case study of a library evacuation in Czech Republic, Poland, Turkey and the UK have been developed to answer this question. Our questionnaire, conducted among 442 respondents (N = 105 from Czech Republic, N = 106 from Poland, N = 106 from Turkey and N = 125 from the United Kingdom), shows significant differences in the number of performed response tasks per culture - whereby Turkish respondents perform the most response tasks and British the least - and the results were directly implemented in our agent-based model. Simulation results show: (1) these differences - in combination with emergent effects for task choice and agent interactions - directly translate into the average response and evacuation times being highest for Turkey, followed by Poland, Czech Republic, and the UK, (2) cues, setting and affiliation influence response and evacuation time - such as being informed by staff giving a negative correlation and evacuating in groups a positive correlation with response time -, while the magnitude of these effects differ per culture. Our results suggest that faster response times might be related to dimensions of national culture, such as weak uncertainty avoidance and high individualism.@en

Emergency evacuation is viewed as a common strategy adopted during the disaster preparedness stage of evacuation to ensure the safety of potentially affected populations. In emergency evacuation studies, soft computing approaches and methodologies have been widely used to support effective decision-making, providing robust and low-cost solutions. To understand the current status and trends of research on soft computing applications for emergency evacuation studies, 778 related studies published in the core database of Web of Science from 2000 to 2020 were considered in this study. A scientometric analysis and a comprehensive review were performed using a scientific mapping of the knowledge domain. This paper presents a set of analyses with the following primary objectives: (1) to explore and visualize the bibliometric characteristics and contents of the academic field concerned with the soft computing approaches for emergency evacuation; and (2) to review and analyze the knowledge, hotspots, and future outlooks related to soft computing approaches for emergency evacuation. The results provide some important insights regarding the existing soft computing methods that have been used in the emergency evacuation field over the past 20 years. Based on the conducted review, this paper proposes that future studies should concentrate on exploring the potential of innovative soft computing approaches for crowd modelling and enabling more accurate evacuation simulation and optimization.@en

In order to explore impacts of crowd intervention strategies on indoor respiratory exposure risks during major pandemics, a variety of crowd motion scenarios were established in general indoor conditions based on improved pedestrian dynamics model and respiratory infection probability model. Then, multi-agent simulation technology was utilized to simulate impacts of strategies, including protection optimization, pedestrian flow optimization and route optimization, on the exposure risks. The results show that indoor respiratory exposure risks are mainly determined by total pedestrian flow, individuals’ stay length, movement route planning and duration of stay in contaminated areas. The carryover effect will be formed due to pedestrians’ obedience behavior of social distancing, which will further increase exposure time to contaminated areas. The lower pathogen permeability of masks, and the greater space ventilation are, the lower infection probability the crowd will face.@en

Emergency services and utilities need appropriate planning tools to analyze and improve infrastructure and community resilience to disasters. Recognized as a key metric of community resilience is the social well-being of a community during a disaster, which is made up of mental and physical social health. Other factors influencing community resilience directly or indirectly are emotional health, emergency services, and the availability of critical infrastructures services, such as food, agriculture, water, transportation, electric power, and communications system. It turns out that in computational social science literature dealing with community resilience, the role of these critical infrastructures along with some important social characteristics is not considered. To address these weaknesses, we develop a new multi-agent based stochastic dynamical model, standardized by overview, design concepts, details, and decision (ODD+D) protocol and derived from neuro-science, psychological and social sciences, to measure community resilience in terms of mental and physical well-being. Using this model, we analyze the micro-macro level dependence between the emergency services and power systems and social characteristics such as fear, risk perception, information-seeking behaviour, cooperation, flexibility, empathy, and experience, in an artificial society. Furthermore, we simulate this model in two case studies and show that a high level of flexibility, experience, and cooperation enhances community resilience. Implications for both theory and practice are discussed. @en

According to the Department of Energy, demand response provides an opportunity for end-users to play a significant role in the efficiency, reliability, resilience, and sustainability of a power grid. This is made possible owing to the existence of storage devices and diversity of energy sources at the customer level and the advent of the Internet of Things. Social influences and psychological traits of consumers affect their behavior and decision-making. Consequently, there is a necessity to bring the influences of humans, organizations, and societies on the power system together through computational social science into a cyber-physical-social system. Hence, in this brief, we introduce our development of an artificial society of the social demand response of a power system, a well-known approach in computational sociology based on a bottom-up approach, starting from theory. We assume that consumers can engage in demand response to fulfill two aims: save their cost or enhance the sustainability of a power system. The literature concerning sustainability-based demand response is limited to only considering CO2, NOX, and SO2. In addition to NOX, and SO2, we examine the impact of power systems on water pollution, disability-adjusted loss of life year, and exergy in demand response, and provide an environomic-based social demand response. We show that when the level of satisfaction and cooperation of end-user is low, the marginal level of load shaving and improvement in sustainability cannot be fulfilled.

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Emergencies such as fires and terrorist attacks pose risks of injuries and fatalities, which can be exacerbated by delayed, ill-informed, or unmanaged responses. Effective emergency communication strategies could be used to better inform people and reduce these risks. This research analyzes videos of real-world emergencies to: (a) identify people's observed behaviors that increase risk during evacuations, and (b) examine which emergency communication strategies might reduce risk behaviors. We analyzed 126 publicly available videos of emergency evacuations in different emergencies (e.g., fire, terror attack, evacuation alarm, perceived threat). We found evidence of three types of risk behaviors (delayed response, filming, running) and four emergency communication strategies (evacuation alarm, staff guiding people to exits, general prerecorded message, live announcement). Our analyses suggest that having staff guide people to exits is the most effective strategy for promoting faster and more effective responses. However, neither live announcements nor pre-recorded messages were associated with delayed responses, while evacuation alarms were associated with more delayed responses than other communication strategies. Although people filming the incident was unrelated to staff interactions, it occurred more with alarms sounding and prerecorded messages, suggesting that these emergency communications might not prevent filming. Compared to no communications, all emergency communication strategies reduced running during evacuations. We discuss the implications of this research for identifying effective emergency communication strategies and reducing risk-increasing evacuation behaviors.

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To improve communication during emergencies, this research introduces an agent-based modeling (ABM) method to test the effect of psychological emergency communication strategies on evacuation performance. We follow a generative social science approach in which agent-based simulations allow for testing different candidate solutions. Unlike traditional methods, such as laboratory experiments and field observations, ABM simulation allows high-risk and infrequent scenarios to be empirically examined before applying the lessons in the real world. This is essential, as emergency communication with diverse crowds can be challenging due to language barriers, con-flicting social identities, different cultural mindsets, and crowd demographics. Improving emergency communication could therefore improve evacuations, reduce injuries, and ultimately save lives. We demonstrate this ABM method by determining the effectiveness of three communication strategies for different crowd compositions in transport terminals: (1) dynamic emergency exit floor lighting directing people to exits, (2) staff guiding people to exits with verbal and physical instructions, and (3) public announcements in English. The simulation results indicated that dynamic emergency exit floor lighting and staff guiding people to exits were only beneficial for high-density crowds and those unfamiliar with the environment. Furthermore, English public announcements actually slowed the evacuation for mainly English-speaking crowds, due to simultaneous egress causing congestion at exits, but improved evacuation speed in multicultural, multilingual crowds. Based on these results, we make recommendations about which communication strategies to apply in the real world to demonstrate the utility of this ABM simulation approach for risk assessment practice.

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Power systems serve social communities that consist of residential, commercial, and industrial customers. As a result, the disaster resilience of a power system should account for social community resilience. The social behavior and psychological features of all stakeholders involved in a disaster influence the level of power system preparedness, mitigation, recovery, adaptability, and resilience. Hence, there is a need to consider the social community's effect on the power system and the dependence between them in determining a power system's resilient to human-made and natural hazards. The social community, such as a county, city, or state, consists of various stakeholders, e.g., social consumers, social prosumers, and utilities. In this paper, we develop a multi-dimensional output-oriented method to measure resilience. The three key ideas for measuring power system resilience are the multi-dimensionality, output-oriented, and degraded functionality aspects of the power system. To this end, we develop an artificial society based on neuroscience, social science, and psychological theories to model the behavior of consumers and prosumers and the interdependence between power system resilience, comsumer and prosumer well-being, and community capital. Both mental health and physical health are used as metrics of well-being, while the level of cooperation is used to measure community capital resilience.@en